#install.packages('TDAmapper')
library(TDAmapper)
library(cluster)
library(vip)
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## 
##     vi
#install.packages('kernlab’)
library(kernlab)
#install.packages(‘class’)
library(class)
#install.packages('nnet')
library(nnet)
#install.packages(‘randomForest’)
library(randomForest)
## randomForest 4.7-1.1
## Type rfNews() to see new features/changes/bug fixes.
#install.packages('e1071')
library(e1071)                                                  
#install.packages("BayesFactor")
library(BayesFactor)
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## ************
## Welcome to BayesFactor 0.9.12-4.5. If you have questions, please contact Richard Morey (richarddmorey@gmail.com).
## 
## Type BFManual() to open the manual.
## ************
library(BayesPPD)
library(bayestestR)
#install.packages('igraph')
library('igraph')
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#install.packages('locfit')
library(locfit)
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library(ggplot2)
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#install.packages('networkD3')
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library(rstanarm)
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## - See https://mc-stan.org/rstanarm/articles/priors for changes to default priors!
## - Default priors may change, so it's safest to specify priors, even if equivalent to the defaults.
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library(see)
#install.packages('tidyverse')
library(tidyverse)
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library(caret)
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## ##
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## ##
#linstall.packages("caret")
library(caret)
library(TDA)
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library(stringr)
#install.packages('ks')
library(ks)
library(GGally)
## Registered S3 method overwritten by 'GGally':
##   method from   
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##Add Bayesian tests functions

#create function to conduct the Bayesian Sign Test
BayesianSignTest <- function(diffVector,rope_min,rope_max) {

  library(MCMCpack)

  samples <- 3000

  #build the vector 0.5 1 1 ....... 1 

  weights <- c(0.5,rep(1,length(diffVector)))

  #add the fake first observation in 0

  diffVector <- c (0, diffVector)  


  #for the moment we implement the sign test. Signedrank will follows

  probLeft <- mean (diffVector < rope_min)

  probRope <- mean (diffVector > rope_min & diffVector < rope_max)

  probRight <- mean (diffVector > rope_max)

  results = list ("probLeft"=probLeft, "probRope"=probRope,
                  
                  "probRight"=probRight)
  
  return (results)
}


##Create function to conduct Bayesian Signed Rank Test

BayesianSignedRank <- function(diffVector,rope_min,rope_max) {
  
  library(MCMCpack)
  
  samples <- 30000
  
  #build the vector 0.5 1 1 ....... 1
  weights <- c(0.5,rep(1,length(diffVector)))
  
  #add the fake first observation in 0
  diffVector <- c (0, diffVector)
  
  sampledWeights <- rdirichlet(samples,weights)
  
  winLeft <- vector(length = samples)
  winRope <- vector(length = samples)
  winRight <- vector(length = samples)
  
  for (rep in 1:samples){
    currentWeights <- sampledWeights[rep,]
    for (i in 1:length(currentWeights)){
      for (j in 1:length(currentWeights)){
        product= currentWeights[i] * currentWeights[j]
        if (diffVector[i]+diffVector[j] > (2*rope_max) ) {
          winRight[rep] <- winRight[rep] + product
        }
        else if (diffVector[i]+diffVector[j] > (2*rope_min) ) {
          winRope[rep] <- winRope[rep] + product
        }
        else {
          winLeft[rep] <- winLeft[rep] + product
        }

      }
    }
    maxWins=max(winRight[rep],winRope[rep],winLeft[rep])
    winners = (winRight[rep]==maxWins)*1 + (winRope[rep]==maxWins)*1 + (winLeft[rep]==maxWins)*1
    winRight[rep] <- (winRight[rep]==maxWins)*1/winners
    winRope[rep] <- (winRope[rep]==maxWins)*1/winners
    winLeft[rep] <- (winLeft[rep]==maxWins)*1/winners
  }
  
  
  results = list ("winLeft"=mean(winLeft), "winRope"=mean(winRope),
                  "winRight"=mean(winRight) )
  return (results)
  
}


#Create function to conduct the Bayesian Correlated t.test

#diff_a_b is a vector of differences between the two classifiers, on each fold of cross-validation.
#If you have done 10 runs of 10-folds cross-validation, you have 100 results for each classifier.
#You should have run cross-validation on the same folds for the two classifiers.
#Then diff_a_b is the difference fold-by-fold.

#rho is the correlation of the cross-validation results: 1/(number of folds)
#rope_min and rope_max are the lower and the upper bound of the rope
 
correlatedBayesianTtest <- function(diff_a_b,rho,rope_min,rope_max){
   if (rope_max < rope_min){
     stop("rope_max should be larger than rope_min")
   }
     
  delta <- mean(diff_a_b)
  n <- length(diff_a_b)
  df <- n-1
  stdX <- sd(diff_a_b)
  sp <- sd(diff_a_b)*sqrt(1/n + rho/(1-rho))
  p.left <- pt((rope_min - delta)/sp, df)
  p.rope <- pt((rope_max - delta)/sp, df)-p.left
  results <- list('left'=p.left,'rope'=p.rope,'right'=1-p.left-p.rope)
  return (results)
}
set.seed(16974)
###################################################5.40.5 ROPE Comparisons for Dissertation

##Random Forest Results

rf_dataset_av<-c(0.8572, 0.9205, 0.9802)

rf_pca.5.40.5_n1_av<-c(0.9929, 0.9078, 0.9994)
rf_pca.5.40.5_n2_av<-c(0.7336, 0.8872, 0.9852)
rf_pca.5.40.5_n3_av<-c(0.8754, 0.9377, 0.9027)
rf_pca.5.40.5_n4_av<-c(0.9644, 0.9743, 0.9770)
rf_pca.5.40.5_n5_av<-c(0.9998, NA, NA)

rf_kde.5.40.5_n1_av<-c(0.8637, 0.9492, 0.9651)
rf_kde.5.40.5_n2_av<-c(0.9998, 0.9460, 0.9860)
rf_kde.5.40.5_n3_av<-c(0.9998, 0.9098, 0.9887)
rf_kde.5.40.5_n4_av<-c(0.9998, 0.8113, 0.9916)
rf_kde.5.40.5_n5_av<-c(0.9998, NA, 0.9916)

   
########################   ROPE PCA

diff_rf_pca.5.40.5_n1_av<-rf_dataset_av - rf_pca.5.40.5_n1_av

bsr_diff_rf_pca.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_rf_pca.5.40.5_n1_av),-0.01,0.01)
bsr_diff_rf_pca.5.40.5_n1_av
## $winLeft
## [1] 0.6768
## 
## $winRope
## [1] 0.2408667
## 
## $winRight
## [1] 0.08233333
bsr_diff_rf_pca.5.40.5_n1_av_odds.left<-bsr_diff_rf_pca.5.40.5_n1_av$winLeft/bsr_diff_rf_pca.5.40.5_n1_av$winRight
bsr_diff_rf_pca.5.40.5_n1_av_odds.left
## [1] 8.220243
plot(rope(diff_rf_pca.5.40.5_n1_av,c(-0.01,0.01)))

diff_rf_pca.5.40.5_n2_av<-rf_dataset_av - rf_pca.5.40.5_n2_av

bsr_diff_rf_pca.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_rf_pca.5.40.5_n2_av),-0.01,0.01)
bsr_diff_rf_pca.5.40.5_n2_av
## $winLeft
## [1] 0
## 
## $winRope
## [1] 0.1469667
## 
## $winRight
## [1] 0.8530333
bsr_diff_rf_pca.5.40.5_n2_av_odds.left<-bsr_diff_rf_pca.5.40.5_n2_av$winLeft/bsr_diff_rf_pca.5.40.5_n2_av$winRight
bsr_diff_rf_pca.5.40.5_n2_av_odds.left
## [1] 0
plot(rope(diff_rf_pca.5.40.5_n2_av,c(-0.01,0.01)))

diff_rf_pca.5.40.5_n3_av<-rf_dataset_av - rf_pca.5.40.5_n3_av

bsr_diff_rf_pca.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_rf_pca.5.40.5_n3_av),-0.01,0.01)
bsr_diff_rf_pca.5.40.5_n3_av
## $winLeft
## [1] 0.3874667
## 
## $winRope
## [1] 0.1308333
## 
## $winRight
## [1] 0.4817
bsr_diff_rf_pca.5.40.5_n3_av_odds.left<-bsr_diff_rf_pca.5.40.5_n3_av$winLeft/bsr_diff_rf_pca.5.40.5_n3_av$winRight
bsr_diff_rf_pca.5.40.5_n3_av_odds.left
## [1] 0.8043734
plot(rope(diff_rf_pca.5.40.5_n3_av,c(-0.01,0.01)))

diff_rf_pca.5.40.5_n4_av<-rf_dataset_av - rf_pca.5.40.5_n4_av

bsr_diff_rf_pca.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_rf_pca.5.40.5_n4_av),-0.01,0.01)
bsr_diff_rf_pca.5.40.5_n4_av
## $winLeft
## [1] 0.8558667
## 
## $winRope
## [1] 0.1441333
## 
## $winRight
## [1] 0
bsr_diff_rf_pca.5.40.5_n4_av_odds.left<-bsr_diff_rf_pca.5.40.5_n4_av$winLeft/bsr_diff_rf_pca.5.40.5_n4_av$winRight
bsr_diff_rf_pca.5.40.5_n4_av_odds.left
## [1] Inf
plot(rope(diff_rf_pca.5.40.5_n4_av,c(-0.01,0.01)))

#diff_rf_pca.5.40.5_n5_av<-rf_dataset_av - rf_pca.5.40.5_n5_av

#bsr_diff_rf_pca.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_rf_pca.5.40.5_n5_av),-0.01,0.01)
#bsr_diff_rf_pca.5.40.5_n5_av

#bsr_diff_rf_pca.5.40.5_n5_av_odds.left<-bsr_diff_rf_pca.5.40.5_n5_av$winLeft/bsr_diff_rf_pca.5.40.5_n5_av$winRight
#bsr_diff_rf_pca.5.40.5_n5_av_odds.left

#plot(rope(diff_rf_pca.5.40.5_n5_av,c(-0.01,0.01)))


##########################    ROPE KDE

diff_rf_kde.5.40.5_n1_av<-rf_dataset_av - rf_kde.5.40.5_n1_av

bsr_diff_rf_kde.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_rf_kde.5.40.5_n1_av),-0.01,0.01)
bsr_diff_rf_kde.5.40.5_n1_av
## $winLeft
## [1] 0.2577
## 
## $winRope
## [1] 0.6879333
## 
## $winRight
## [1] 0.05436667
bsr_diff_rf_kde.5.40.5_n1_av_odds.left<-bsr_diff_rf_kde.5.40.5_n1_av$winLeft/bsr_diff_rf_kde.5.40.5_n1_av$winRight
bsr_diff_rf_kde.5.40.5_n1_av_odds.left
## [1] 4.740037
plot(rope(diff_rf_kde.5.40.5_n1_av,c(-0.01,0.01)))

diff_rf_kde.5.40.5_n2_av<-rf_dataset_av - rf_kde.5.40.5_n2_av

bsr_diff_rf_kde.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_rf_kde.5.40.5_n2_av),-0.01,0.01)
bsr_diff_rf_kde.5.40.5_n2_av
## $winLeft
## [1] 0.8571667
## 
## $winRope
## [1] 0.1428333
## 
## $winRight
## [1] 0
bsr_diff_rf_kde.5.40.5_n2_av_odds.left<-bsr_diff_rf_kde.5.40.5_n2_av$winLeft/bsr_diff_rf_kde.5.40.5_n2_av$winRight
bsr_diff_rf_kde.5.40.5_n2_av_odds.left
## [1] Inf
plot(rope(diff_rf_kde.5.40.5_n2_av,c(-0.01,0.01)))

diff_rf_kde.5.40.5_n3_av<-rf_dataset_av - rf_kde.5.40.5_n3_av

bsr_diff_rf_kde.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_rf_kde.5.40.5_n3_av),-0.01,0.01)
bsr_diff_rf_kde.5.40.5_n3_av
## $winLeft
## [1] 0.4713333
## 
## $winRope
## [1] 0.4522
## 
## $winRight
## [1] 0.07646667
bsr_diff_rf_kde.5.40.5_n3_av_odds.left<-bsr_diff_rf_kde.5.40.5_n3_av$winLeft/bsr_diff_rf_kde.5.40.5_n3_av$winRight
bsr_diff_rf_kde.5.40.5_n3_av_odds.left
## [1] 6.163906
plot(rope(diff_rf_kde.5.40.5_n3_av,c(-0.01,0.01)))

diff_rf_kde.5.40.5_n4_av<-rf_dataset_av - rf_kde.5.40.5_n4_av

bsr_diff_rf_kde.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_rf_kde.5.40.5_n4_av),-0.01,0.01)
bsr_diff_rf_kde.5.40.5_n4_av
## $winLeft
## [1] 0.6637333
## 
## $winRope
## [1] 0.0595
## 
## $winRight
## [1] 0.2767667
bsr_diff_rf_kde.5.40.5_n4_av_odds.left<-bsr_diff_rf_kde.5.40.5_n4_av$winLeft/bsr_diff_rf_kde.5.40.5_n4_av$winRight
bsr_diff_rf_kde.5.40.5_n4_av_odds.left
## [1] 2.398169
plot(rope(diff_rf_kde.5.40.5_n4_av,c(-0.01,0.01)))

#diff_rf_kde.5.40.5_n5_av<-rf_dataset_av - rf_kde.5.40.5_n5_av

#bsr_diff_rf_kde.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_rf_kde.5.40.5_n5_av),-0.01,0.01)
#bsr_diff_rf_kde.5.40.5_n5_av

#bsr_diff_rf_kde.5.40.5_n5_av_odds.left<-bsr_diff_rf_kde.5.40.5_n5_av$winLeft/bsr_diff_rf_kde.5.40.5_n5_av$winRight
#bsr_diff_rf_kde.5.40.5_n5_av_odds.left

#plot(rope(diff_rf_kde.5.40.5_n5_av,c(-0.01,0.01)))


################################  Support Vector Machine

##Support Vector Machine Results

svm_dataset_av<-c(0.8238, 0.9312, 0.9796)

svm_pca.5.40.5_n1_av<-c(0.6960, 0.9160, 0.9994)
svm_pca.5.40.5_n2_av<-c(0.6987, 0.8937, 0.9850)
svm_pca.5.40.5_n3_av<-c(0.8283, 0.8040, 0.9109)
svm_pca.5.40.5_n4_av<-c(0.9579, 0.9844, 0.9820)
svm_pca.5.40.5_n5_av<-c(0.9997, NA, NA)

svm_kde.5.40.5_n1_av<-c(0.8126, 0.9528, 0.9887)
svm_kde.5.40.5_n2_av<-c(0.8038, 0.9487, 0.9783)
svm_kde.5.40.5_n3_av<-c(0.7938, 0.6117, 0.9861)
svm_kde.5.40.5_n4_av<-c(0.8388, 0.8181, 0.9892)
svm_kde.5.40.5_n5_av<-c(0.7989, 0.6499, 0.9909)

   
########################   ROPE PCA

diff_svm_pca.5.40.5_n1_av<-svm_dataset_av - svm_pca.5.40.5_n1_av

bsr_diff_svm_pca.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_svm_pca.5.40.5_n1_av),-0.01,0.01)
bsr_diff_svm_pca.5.40.5_n1_av
## $winLeft
## [1] 0.07993333
## 
## $winRope
## [1] 0.2493333
## 
## $winRight
## [1] 0.6707333
bsr_diff_svm_pca.5.40.5_n1_av_odds.left<-bsr_diff_svm_pca.5.40.5_n1_av$winLeft/bsr_diff_svm_pca.5.40.5_n1_av$winRight
bsr_diff_svm_pca.5.40.5_n1_av_odds.left
## [1] 0.119173
plot(rope(diff_svm_pca.5.40.5_n1_av,c(-0.01,0.01)))

diff_svm_pca.5.40.5_n2_av<-svm_dataset_av - svm_pca.5.40.5_n2_av

bsr_diff_svm_pca.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_svm_pca.5.40.5_n2_av),-0.01,0.01)
bsr_diff_svm_pca.5.40.5_n2_av
## $winLeft
## [1] 0
## 
## $winRope
## [1] 0.1454333
## 
## $winRight
## [1] 0.8545667
bsr_diff_svm_pca.5.40.5_n2_av_odds.left<-bsr_diff_svm_pca.5.40.5_n2_av$winLeft/bsr_diff_svm_pca.5.40.5_n2_av$winRight
bsr_diff_svm_pca.5.40.5_n2_av_odds.left
## [1] 0
plot(rope(diff_svm_pca.5.40.5_n2_av,c(-0.01,0.01)))

diff_svm_pca.5.40.5_n3_av<-svm_dataset_av - svm_pca.5.40.5_n3_av

bsr_diff_svm_pca.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_svm_pca.5.40.5_n3_av),-0.01,0.01)
bsr_diff_svm_pca.5.40.5_n3_av
## $winLeft
## [1] 0
## 
## $winRope
## [1] 0.1432
## 
## $winRight
## [1] 0.8568
bsr_diff_svm_pca.5.40.5_n3_av_odds.left<-bsr_diff_svm_pca.5.40.5_n3_av$winLeft/bsr_diff_svm_pca.5.40.5_n3_av$winRight
bsr_diff_svm_pca.5.40.5_n3_av_odds.left
## [1] 0
plot(rope(diff_svm_pca.5.40.5_n3_av,c(-0.01,0.01)))

diff_svm_pca.5.40.5_n4_av<-svm_dataset_av - svm_pca.5.40.5_n4_av

bsr_diff_svm_pca.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_svm_pca.5.40.5_n4_av),-0.01,0.01)
bsr_diff_svm_pca.5.40.5_n4_av
## $winLeft
## [1] 0.8562
## 
## $winRope
## [1] 0.1438
## 
## $winRight
## [1] 0
bsr_diff_svm_pca.5.40.5_n4_av_odds.left<-bsr_diff_svm_pca.5.40.5_n4_av$winLeft/bsr_diff_svm_pca.5.40.5_n4_av$winRight
bsr_diff_svm_pca.5.40.5_n4_av_odds.left
## [1] Inf
plot(rope(diff_svm_pca.5.40.5_n4_av,c(-0.01,0.01)))

#diff_svm_pca.5.40.5_n5_av<-svm_dataset_av - svm_pca.5.40.5_n5_av

#bsr_diff_svm_pca.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_svm_pca.5.40.5_n5_av),-0.01,0.01)
#bsr_diff_svm_pca.5.40.5_n5_av

#bsr_diff_svm_pca.5.40.5_n5_av_odds.left<-bsr_diff_svm_pca.5.40.5_n5_av$winLeft/bsr_diff_svm_pca.5.40.5_n5_av$winRight
#bsr_diff_svm_pca.5.40.5_n5_av_odds.left

#plot(rope(diff_svm_pca.5.40.5_n5_av,c(-0.01,0.01)))


##########################    ROPE KDE

diff_svm_kde.5.40.5_n1_av<-svm_dataset_av - svm_kde.5.40.5_n1_av

bsr_diff_svm_kde.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_svm_kde.5.40.5_n1_av),-0.01,0.01)
bsr_diff_svm_kde.5.40.5_n1_av
## $winLeft
## [1] 0.2546667
## 
## $winRope
## [1] 0.6896
## 
## $winRight
## [1] 0.05573333
bsr_diff_svm_kde.5.40.5_n1_av_odds.left<-bsr_diff_svm_kde.5.40.5_n1_av$winLeft/bsr_diff_svm_kde.5.40.5_n1_av$winRight
bsr_diff_svm_kde.5.40.5_n1_av_odds.left
## [1] 4.569378
plot(rope(diff_svm_kde.5.40.5_n1_av,c(-0.01,0.01)))

diff_svm_kde.5.40.5_n2_av<-svm_dataset_av - svm_kde.5.40.5_n2_av

bsr_diff_svm_kde.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_svm_kde.5.40.5_n2_av),-0.01,0.01)
bsr_diff_svm_kde.5.40.5_n2_av
## $winLeft
## [1] 0.05573333
## 
## $winRope
## [1] 0.6868333
## 
## $winRight
## [1] 0.2574333
bsr_diff_svm_kde.5.40.5_n2_av_odds.left<-bsr_diff_svm_kde.5.40.5_n2_av$winLeft/bsr_diff_svm_kde.5.40.5_n2_av$winRight
bsr_diff_svm_kde.5.40.5_n2_av_odds.left
## [1] 0.2164962
plot(rope(diff_svm_kde.5.40.5_n2_av,c(-0.01,0.01)))

diff_svm_kde.5.40.5_n3_av<-svm_dataset_av - svm_kde.5.40.5_n3_av

bsr_diff_svm_kde.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_svm_kde.5.40.5_n3_av),-0.01,0.01)
bsr_diff_svm_kde.5.40.5_n3_av
## $winLeft
## [1] 0
## 
## $winRope
## [1] 0.1447667
## 
## $winRight
## [1] 0.8552333
bsr_diff_svm_kde.5.40.5_n3_av_odds.left<-bsr_diff_svm_kde.5.40.5_n3_av$winLeft/bsr_diff_svm_kde.5.40.5_n3_av$winRight
bsr_diff_svm_kde.5.40.5_n3_av_odds.left
## [1] 0
plot(rope(diff_svm_kde.5.40.5_n3_av,c(-0.01,0.01)))

diff_svm_kde.5.40.5_n4_av<-svm_dataset_av - svm_kde.5.40.5_n4_av

bsr_diff_svm_kde.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_svm_kde.5.40.5_n4_av),-0.01,0.01)
bsr_diff_svm_kde.5.40.5_n4_av
## $winLeft
## [1] 0.2174333
## 
## $winRope
## [1] 0.2854333
## 
## $winRight
## [1] 0.4971333
bsr_diff_svm_kde.5.40.5_n4_av_odds.left<-bsr_diff_svm_kde.5.40.5_n4_av$winLeft/bsr_diff_svm_kde.5.40.5_n4_av$winRight
bsr_diff_svm_kde.5.40.5_n4_av_odds.left
## [1] 0.4373743
plot(rope(diff_svm_kde.5.40.5_n4_av,c(-0.01,0.01)))

diff_svm_kde.5.40.5_n5_av<-svm_dataset_av - svm_kde.5.40.5_n5_av

bsr_diff_svm_kde.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_svm_kde.5.40.5_n5_av),-0.01,0.01)
bsr_diff_svm_kde.5.40.5_n5_av
## $winLeft
## [1] 0.0837
## 
## $winRope
## [1] 0.1416667
## 
## $winRight
## [1] 0.7746333
bsr_diff_svm_kde.5.40.5_n5_av_odds.left<-bsr_diff_svm_kde.5.40.5_n5_av$winLeft/bsr_diff_svm_kde.5.40.5_n5_av$winRight
bsr_diff_svm_kde.5.40.5_n5_av_odds.left
## [1] 0.1080511
plot(rope(diff_svm_kde.5.40.5_n5_av,c(-0.01,0.01)))

#########################  Neural Network

##Neural Network Results

nn1_dataset_av<-c(0.8200, 0.4913, 0.9806)

nn1_pca.5.40.5_n1_av<-c(0.9923, 0.8828, 0.9994)
nn1_pca.5.40.5_n2_av<-c(0.6729, 0.6380, 0.9851)
nn1_pca.5.40.5_n3_av<-c(0.8628, 0.6827, 0.8962)
nn1_pca.5.40.5_n4_av<-c(0.9635, 0.9542, 0.9820)
nn1_pca.5.40.5_n5_av<-c(0.9997, NA, NA)

nn1_kde.5.40.5_n1_av<-c(0.8567, 0.6145, 0.9665)
nn1_kde.5.40.5_n2_av<-c(0.8074, 0.7469, 0.9851)
nn1_kde.5.40.5_n3_av<-c(0.8064, 0.6686, 0.9852)
nn1_kde.5.40.5_n4_av<-c(0.8469, 0.7828, 0.9887)
nn1_kde.5.40.5_n5_av<-c(0.8702, 0.6681, 0.9909)

   
########################   ROPE PCA

diff_nn1_pca.5.40.5_n1_av<-nn1_dataset_av - nn1_pca.5.40.5_n1_av

bsr_diff_nn1_pca.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_nn1_pca.5.40.5_n1_av),-0.01,0.01)
bsr_diff_nn1_pca.5.40.5_n1_av
## $winLeft
## [1] 0.9621667
## 
## $winRope
## [1] 0.03783333
## 
## $winRight
## [1] 0
bsr_diff_nn1_pca.5.40.5_n1_av_odds.left<-bsr_diff_nn1_pca.5.40.5_n1_av$winLeft/bsr_diff_nn1_pca.5.40.5_n1_av$winRight
bsr_diff_nn1_pca.5.40.5_n1_av_odds.left
## [1] Inf
plot(rope(diff_nn1_pca.5.40.5_n1_av,c(-0.01,0.01)))

diff_nn1_pca.5.40.5_n2_av<-nn1_dataset_av - nn1_pca.5.40.5_n2_av

bsr_diff_nn1_pca.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_nn1_pca.5.40.5_n2_av),-0.01,0.01)
bsr_diff_nn1_pca.5.40.5_n2_av
## $winLeft
## [1] 0.3465
## 
## $winRope
## [1] 0.3081333
## 
## $winRight
## [1] 0.3453667
bsr_diff_nn1_pca.5.40.5_n2_av_odds.left<-bsr_diff_nn1_pca.5.40.5_n2_av$winLeft/bsr_diff_nn1_pca.5.40.5_n2_av$winRight
bsr_diff_nn1_pca.5.40.5_n2_av_odds.left
## [1] 1.003282
plot(rope(diff_nn1_pca.5.40.5_n2_av,c(-0.01,0.01)))

diff_nn1_pca.5.40.5_n3_av<-nn1_dataset_av - nn1_pca.5.40.5_n3_av

bsr_diff_nn1_pca.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_nn1_pca.5.40.5_n3_av),-0.01,0.01)
bsr_diff_nn1_pca.5.40.5_n3_av
## $winLeft
## [1] 0.7283333
## 
## $winRope
## [1] 0.01686667
## 
## $winRight
## [1] 0.2548
bsr_diff_nn1_pca.5.40.5_n3_av_odds.left<-bsr_diff_nn1_pca.5.40.5_n3_av$winLeft/bsr_diff_nn1_pca.5.40.5_n3_av$winRight
bsr_diff_nn1_pca.5.40.5_n3_av_odds.left
## [1] 2.858451
plot(rope(diff_nn1_pca.5.40.5_n3_av,c(-0.01,0.01)))

diff_nn1_pca.5.40.5_n4_av<-nn1_dataset_av - nn1_pca.5.40.5_n4_av

bsr_diff_nn1_pca.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_nn1_pca.5.40.5_n4_av),-0.01,0.01)
bsr_diff_nn1_pca.5.40.5_n4_av
## $winLeft
## [1] 0.8593667
## 
## $winRope
## [1] 0.1406333
## 
## $winRight
## [1] 0
bsr_diff_nn1_pca.5.40.5_n4_av_odds.left<-bsr_diff_nn1_pca.5.40.5_n4_av$winLeft/bsr_diff_nn1_pca.5.40.5_n4_av$winRight
bsr_diff_nn1_pca.5.40.5_n4_av_odds.left
## [1] Inf
plot(rope(diff_nn1_pca.5.40.5_n4_av,c(-0.01,0.01)))

#diff_nn1_pca.5.40.5_n5_av<-nn1_dataset_av - nn1_pca.5.40.5_n5_av

#bsr_diff_nn1_pca.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_nn1_pca.5.40.5_n5_av),-0.01,0.01)
#bsr_diff_nn1_pca.5.40.5_n5_av

#bsr_diff_nn1_pca.5.40.5_n5_av_odds.left<-bsr_diff_nn1_pca.5.40.5_n5_av$winLeft/bsr_diff_nn1_pca.5.40.5_n5_av$winRight
#bsr_diff_nn1_pca.5.40.5_n5_av_odds.left

#plot(rope(diff_nn1_pca.5.40.5_n5_av,c(-0.01,0.01)))


##########################    ROPE KDE

diff_nn1_kde.5.40.5_n1_av<-nn1_dataset_av - nn1_kde.5.40.5_n1_av

bsr_diff_nn1_kde.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_nn1_kde.5.40.5_n1_av),-0.01,0.01)
bsr_diff_nn1_kde.5.40.5_n1_av
## $winLeft
## [1] 0.8869333
## 
## $winRope
## [1] 0.0519
## 
## $winRight
## [1] 0.06116667
bsr_diff_nn1_kde.5.40.5_n1_av_odds.left<-bsr_diff_nn1_kde.5.40.5_n1_av$winLeft/bsr_diff_nn1_kde.5.40.5_n1_av$winRight
bsr_diff_nn1_kde.5.40.5_n1_av_odds.left
## [1] 14.50027
plot(rope(diff_nn1_kde.5.40.5_n1_av,c(-0.01,0.01)))

diff_nn1_kde.5.40.5_n2_av<-nn1_dataset_av - nn1_kde.5.40.5_n2_av

bsr_diff_nn1_kde.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_nn1_kde.5.40.5_n2_av),-0.01,0.01)
bsr_diff_nn1_kde.5.40.5_n2_av
## $winLeft
## [1] 0.4739667
## 
## $winRope
## [1] 0.4505
## 
## $winRight
## [1] 0.07553333
bsr_diff_nn1_kde.5.40.5_n2_av_odds.left<-bsr_diff_nn1_kde.5.40.5_n2_av$winLeft/bsr_diff_nn1_kde.5.40.5_n2_av$winRight
bsr_diff_nn1_kde.5.40.5_n2_av_odds.left
## [1] 6.274934
plot(rope(diff_nn1_kde.5.40.5_n2_av,c(-0.01,0.01)))

diff_nn1_kde.5.40.5_n3_av<-nn1_dataset_av - nn1_kde.5.40.5_n3_av

bsr_diff_nn1_kde.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_nn1_kde.5.40.5_n3_av),-0.01,0.01)
bsr_diff_nn1_kde.5.40.5_n3_av
## $winLeft
## [1] 0.479
## 
## $winRope
## [1] 0.4470333
## 
## $winRight
## [1] 0.07396667
bsr_diff_nn1_kde.5.40.5_n3_av_odds.left<-bsr_diff_nn1_kde.5.40.5_n3_av$winLeft/bsr_diff_nn1_kde.5.40.5_n3_av$winRight
bsr_diff_nn1_kde.5.40.5_n3_av_odds.left
## [1] 6.47589
plot(rope(diff_nn1_kde.5.40.5_n3_av,c(-0.01,0.01)))

diff_nn1_kde.5.40.5_n4_av<-nn1_dataset_av - nn1_kde.5.40.5_n4_av

bsr_diff_nn1_kde.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_nn1_kde.5.40.5_n4_av),-0.01,0.01)
bsr_diff_nn1_kde.5.40.5_n4_av
## $winLeft
## [1] 0.8566333
## 
## $winRope
## [1] 0.1433667
## 
## $winRight
## [1] 0
bsr_diff_nn1_kde.5.40.5_n4_av_odds.left<-bsr_diff_nn1_kde.5.40.5_n4_av$winLeft/bsr_diff_nn1_kde.5.40.5_n4_av$winRight
bsr_diff_nn1_kde.5.40.5_n4_av_odds.left
## [1] Inf
plot(rope(diff_nn1_kde.5.40.5_n4_av,c(-0.01,0.01)))

diff_nn1_kde.5.40.5_n5_av<-nn1_dataset_av - nn1_kde.5.40.5_n5_av

bsr_diff_nn1_kde.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_nn1_kde.5.40.5_n5_av),-0.01,0.01)
bsr_diff_nn1_kde.5.40.5_n5_av
## $winLeft
## [1] 0.9630333
## 
## $winRope
## [1] 0.03696667
## 
## $winRight
## [1] 0
bsr_diff_nn1_kde.5.40.5_n5_av_odds.left<-bsr_diff_nn1_kde.5.40.5_n5_av$winLeft/bsr_diff_nn1_kde.5.40.5_n5_av$winRight
bsr_diff_nn1_kde.5.40.5_n5_av_odds.left
## [1] Inf
plot(rope(diff_nn1_kde.5.40.5_n5_av,c(-0.01,0.01)))

################################  Logistic Regression

##Logistic Rergression Results

lr_dataset_av<-c(0.8511, 0.9262, 0.9797)

lr_pca.5.40.5_n1_av<-c(0.9671, 0.9262, 0.9994)
lr_pca.5.40.5_n2_av<-c(0.6710, 0.9262, 0.9845)
lr_pca.5.40.5_n3_av<-c(0.8642, 0.9262, 0.8767)
lr_pca.5.40.5_n4_av<-c(0.9437, 0.9799, 0.9830)
lr_pca.5.40.5_n5_av<-c(0.9834, NA, NA)

lr_kde.5.40.5_n1_av<-c(0.8202, 0.9491, 0.9632)
lr_kde.5.40.5_n2_av<-c(0.8427, 0.9493, 0.9795)
lr_kde.5.40.5_n3_av<-c(0.8308, 0.9120, 0.9861)
lr_kde.5.40.5_n4_av<-c(0.8612, 0.8181, 0.9890)
lr_kde.5.40.5_n5_av<-c(0.8636, 0.7364, 0.9902)

   
########################   ROPE PCA

diff_lr_pca.5.40.5_n1_av<-lr_dataset_av - lr_pca.5.40.5_n1_av

bsr_diff_lr_pca.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_lr_pca.5.40.5_n1_av),-0.01,0.01)
bsr_diff_lr_pca.5.40.5_n1_av
## $winLeft
## [1] 0.6067667
## 
## $winRope
## [1] 0.3932333
## 
## $winRight
## [1] 0
bsr_diff_lr_pca.5.40.5_n1_av_odds.left<-bsr_diff_lr_pca.5.40.5_n1_av$winLeft/bsr_diff_lr_pca.5.40.5_n1_av$winRight
bsr_diff_lr_pca.5.40.5_n1_av_odds.left
## [1] Inf
plot(rope(diff_lr_pca.5.40.5_n1_av,c(-0.01,0.01)))

diff_lr_pca.5.40.5_n2_av<-lr_dataset_av - lr_pca.5.40.5_n2_av

bsr_diff_lr_pca.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_lr_pca.5.40.5_n2_av),-0.01,0.01)
bsr_diff_lr_pca.5.40.5_n2_av
## $winLeft
## [1] 0
## 
## $winRope
## [1] 0.5792667
## 
## $winRight
## [1] 0.4207333
bsr_diff_lr_pca.5.40.5_n2_av_odds.left<-bsr_diff_lr_pca.5.40.5_n2_av$winLeft/bsr_diff_lr_pca.5.40.5_n2_av$winRight
bsr_diff_lr_pca.5.40.5_n2_av_odds.left
## [1] 0
plot(rope(diff_lr_pca.5.40.5_n2_av,c(-0.01,0.01)))

diff_lr_pca.5.40.5_n3_av<-lr_dataset_av - lr_pca.5.40.5_n3_av

bsr_diff_lr_pca.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_lr_pca.5.40.5_n3_av),-0.01,0.01)
bsr_diff_lr_pca.5.40.5_n3_av
## $winLeft
## [1] 0.0771
## 
## $winRope
## [1] 0.447
## 
## $winRight
## [1] 0.4759
bsr_diff_lr_pca.5.40.5_n3_av_odds.left<-bsr_diff_lr_pca.5.40.5_n3_av$winLeft/bsr_diff_lr_pca.5.40.5_n3_av$winRight
bsr_diff_lr_pca.5.40.5_n3_av_odds.left
## [1] 0.1620088
plot(rope(diff_lr_pca.5.40.5_n3_av,c(-0.01,0.01)))

diff_lr_pca.5.40.5_n4_av<-lr_dataset_av - lr_pca.5.40.5_n4_av

bsr_diff_lr_pca.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_lr_pca.5.40.5_n4_av),-0.01,0.01)
bsr_diff_lr_pca.5.40.5_n4_av
## $winLeft
## [1] 0.8538667
## 
## $winRope
## [1] 0.1461333
## 
## $winRight
## [1] 0
bsr_diff_lr_pca.5.40.5_n4_av_odds.left<-bsr_diff_lr_pca.5.40.5_n4_av$winLeft/bsr_diff_lr_pca.5.40.5_n4_av$winRight
bsr_diff_lr_pca.5.40.5_n4_av_odds.left
## [1] Inf
plot(rope(diff_lr_pca.5.40.5_n4_av,c(-0.01,0.01)))

#diff_lr_pca.5.40.5_n5_av<-lr_dataset_av - lr_pca.5.40.5_n5_av

#bsr_diff_lr_pca.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_lr_pca.5.40.5_n5_av),-0.01,0.01)
#bsr_diff_lr_pca.5.40.5_n5_av

#bsr_diff_lr_pca.5.40.5_n5_av_odds.left<-bsr_diff_lr_pca.5.40.5_n5_av$winLeft/bsr_diff_lr_pca.5.40.5_n5_av$winRight
#bsr_diff_lr_pca.5.40.5_n5_av_odds.left

#plot(rope(diff_lr_pca.5.40.5_n5_av,c(-0.01,0.01)))


##########################    ROPE KDE

diff_lr_kde.5.40.5_n1_av<-lr_dataset_av - lr_kde.5.40.5_n1_av

bsr_diff_lr_kde.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_lr_kde.5.40.5_n1_av),-0.01,0.01)
bsr_diff_lr_kde.5.40.5_n1_av
## $winLeft
## [1] 0.1349667
## 
## $winRope
## [1] 0.3734333
## 
## $winRight
## [1] 0.4916
bsr_diff_lr_kde.5.40.5_n1_av_odds.left<-bsr_diff_lr_kde.5.40.5_n1_av $winLeft/bsr_diff_lr_kde.5.40.5_n1_av$winRight
bsr_diff_lr_kde.5.40.5_n1_av_odds.left
## [1] 0.2745457
plot(rope(diff_lr_kde.5.40.5_n1_av,c(-0.01,0.01)))

diff_lr_kde.5.40.5_n2_av<-lr_dataset_av - lr_kde.5.40.5_n2_av

bsr_diff_lr_kde.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_lr_kde.5.40.5_n2_av),-0.01,0.01)
bsr_diff_lr_kde.5.40.5_n2_av
## $winLeft
## [1] 0.2336
## 
## $winRope
## [1] 0.7664
## 
## $winRight
## [1] 0
bsr_diff_lr_kde.5.40.5_n2_av_odds.left<-bsr_diff_lr_kde.5.40.5_n2_av $winLeft/bsr_diff_lr_kde.5.40.5_n2_av$winRight
bsr_diff_lr_kde.5.40.5_n2_av_odds.left
## [1] Inf
plot(rope(diff_lr_kde.5.40.5_n2_av,c(-0.01,0.01)))

diff_lr_kde.5.40.5_n3_av<-lr_dataset_av - lr_kde.5.40.5_n3_av

bsr_diff_lr_kde.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_lr_kde.5.40.5_n3_av),-0.01,0.01)
bsr_diff_lr_kde.5.40.5_n3_av
## $winLeft
## [1] 0
## 
## $winRope
## [1] 0.5791333
## 
## $winRight
## [1] 0.4208667
bsr_diff_lr_kde.5.40.5_n3_av_odds.left<-bsr_diff_lr_kde.5.40.5_n3_av $winLeft/bsr_diff_lr_kde.5.40.5_n3_av$winRight
bsr_diff_lr_kde.5.40.5_n3_av_odds.left
## [1] 0
plot(rope(diff_lr_kde.5.40.5_n3_av,c(-0.01,0.01)))

diff_lr_kde.5.40.5_n4_av<-lr_dataset_av - lr_kde.5.40.5_n4_av

bsr_diff_lr_kde.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_lr_kde.5.40.5_n4_av),-0.01,0.01)
bsr_diff_lr_kde.5.40.5_n4_av
## $winLeft
## [1] 0.0753
## 
## $winRope
## [1] 0.4555667
## 
## $winRight
## [1] 0.4691333
bsr_diff_lr_kde.5.40.5_n4_av_odds.left<-bsr_diff_lr_kde.5.40.5_n4_av $winLeft/bsr_diff_lr_kde.5.40.5_n4_av$winRight
bsr_diff_lr_kde.5.40.5_n4_av_odds.left
## [1] 0.1605087
plot(rope(diff_lr_kde.5.40.5_n4_av,c(-0.01,0.01)))

diff_lr_kde.5.40.5_n5_av<-lr_dataset_av - lr_kde.5.40.5_n5_av

bsr_diff_lr_kde.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_lr_kde.5.40.5_n5_av),-0.01,0.01)
bsr_diff_lr_kde.5.40.5_n5_av
## $winLeft
## [1] 0.3860667
## 
## $winRope
## [1] 0.1281
## 
## $winRight
## [1] 0.4858333
bsr_diff_lr_kde.5.40.5_n5_av_odds.left<-bsr_diff_lr_kde.5.40.5_n5_av $winLeft/bsr_diff_lr_kde.5.40.5_n5_av$winRight
bsr_diff_lr_kde.5.40.5_n5_av_odds.left
## [1] 0.7946484
plot(rope(diff_lr_kde.5.40.5_n5_av,c(-0.01,0.01)))

####################################################   Naive Bayes

##Naive Bayes Results

nb_dataset_av<-c(0.7666, 0.9028, 0.9621)

nb_pca.5.40.5_n1_av<-c(0.9923, 0.8348, 0.9736)
nb_pca.5.40.5_n2_av<-c(0.6108, 0.8589, 0.9541)
nb_pca.5.40.5_n3_av<-c(0.7917, NA, 0.7794)
nb_pca.5.40.5_n4_av<-c(0.9574, 0.9743, 0.9102)
nb_pca.5.40.5_n5_av<-c(0.9997, NA, NA)

nb_kde.5.40.5_n1_av<-c(0.7522, 0.9162, 0.9489)
nb_kde.5.40.5_n2_av<-c(0.6108, 0.8586, 0.9385)
nb_kde.5.40.5_n3_av<-c(0.7917, NA, 0.7820)
nb_kde.5.40.5_n4_av<-c(0.9574, 0.9687, 0.9162)
nb_kde.5.40.5_n5_av<-c(0.9997, NA, NA)

   
########################   ROPE PCA

diff_nb_pca.5.40.5_n1_av<-nb_dataset_av - nb_pca.5.40.5_n1_av

bsr_diff_nb_pca.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_nb_pca.5.40.5_n1_av),-0.01,0.01)
bsr_diff_nb_pca.5.40.5_n1_av
## $winLeft
## [1] 0.6617
## 
## $winRope
## [1] 0.06063333
## 
## $winRight
## [1] 0.2776667
bsr_diff_nb_pca.5.40.5_n1_av_odds.left<-bsr_diff_nb_pca.5.40.5_n1_av$winLeft/bsr_diff_nb_pca.5.40.5_n1_av$winRight
bsr_diff_nb_pca.5.40.5_n1_av_odds.left
## [1] 2.383073
plot(rope(diff_nb_pca.5.40.5_n1_av,c(-0.01,0.01)))

diff_nb_pca.5.40.5_n2_av<-nb_dataset_av - nb_pca.5.40.5_n2_av

bsr_diff_nb_pca.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_nb_pca.5.40.5_n2_av),-0.01,0.01)
bsr_diff_nb_pca.5.40.5_n2_av
## $winLeft
## [1] 0
## 
## $winRope
## [1] 0.1429
## 
## $winRight
## [1] 0.8571
bsr_diff_nb_pca.5.40.5_n2_av_odds.left<-bsr_diff_nb_pca.5.40.5_n2_av$winLeft/bsr_diff_nb_pca.5.40.5_n2_av$winRight
bsr_diff_nb_pca.5.40.5_n2_av_odds.left
## [1] 0
plot(rope(diff_nb_pca.5.40.5_n2_av,c(-0.01,0.01)))

#diff_nb_pca.5.40.5_n3_av<-nb_dataset_av - nb_pca.5.40.5_n3_av

#bsr_diff_nb_pca.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_nb_pca.5.40.5_n3_av),-0.01,0.01)
#bsr_diff_nb_pca.5.40.5_n3_av

#bsr_diff_nb_pca.5.40.5_n3_av_odds.left<-bsr_diff_nb_pca.5.40.5_n3_av$winLeft/bsr_diff_nb_pca.5.40.5_n3_av$winRight
#bsr_diff_nb_pca.5.40.5_n3_av_odds.left

#plot(rope(diff_nb_pca.5.40.5_n3_av,c(-0.01,0.01)))


diff_nb_pca.5.40.5_n4_av<-nb_dataset_av - nb_pca.5.40.5_n4_av

bsr_diff_nb_pca.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_nb_pca.5.40.5_n4_av),-0.01,0.01)
bsr_diff_nb_pca.5.40.5_n4_av
## $winLeft
## [1] 0.7998667
## 
## $winRope
## [1] 0.04733333
## 
## $winRight
## [1] 0.1528
bsr_diff_nb_pca.5.40.5_n4_av_odds.left<-bsr_diff_nb_pca.5.40.5_n4_av$winLeft/bsr_diff_nb_pca.5.40.5_n4_av$winRight
bsr_diff_nb_pca.5.40.5_n4_av_odds.left
## [1] 5.234729
plot(rope(diff_nb_pca.5.40.5_n4_av,c(-0.01,0.01)))

#diff_nb_pca.5.40.5_n5_av<-nb_dataset_av - nb_pca.5.40.5_n5_av

#bsr_diff_nb_pca.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_nb_pca.5.40.5_n5_av),-0.01,0.01)
#bsr_diff_nb_pca.5.40.5_n5_av

#bsr_diff_nb_pca.5.40.5_n5_av_odds.left<-bsr_diff_nb_pca.5.40.5_n5_av$winLeft/bsr_diff_nb_pca.5.40.5_n5_av$winRight
#bsr_diff_nb_pca.5.40.5_n5_av_odds.left

#plot(rope(diff_nb_pca.5.40.5_n5_av,c(-0.01,0.01)))


##########################    ROPE KDE

diff_nb_kde.5.40.5_n1_av<-nb_dataset_av - nb_kde.5.40.5_n1_av

bsr_diff_nb_kde.5.40.5_n1_av<-BayesianSignedRank(as.matrix(diff_nb_kde.5.40.5_n1_av),-0.01,0.01)
bsr_diff_nb_kde.5.40.5_n1_av
## $winLeft
## [1] 0.05703333
## 
## $winRope
## [1] 0.5852667
## 
## $winRight
## [1] 0.3577
bsr_diff_nb_kde.5.40.5_n1_av_odds.left<-bsr_diff_nb_kde.5.40.5_n1_av$winLeft/bsr_diff_nb_kde.5.40.5_n1_av$winRight
bsr_diff_nb_kde.5.40.5_n1_av_odds.left
## [1] 0.1594446
plot(rope(diff_nb_kde.5.40.5_n1_av,c(-0.01,0.01)))

diff_nb_kde.5.40.5_n2_av<-nb_dataset_av - nb_kde.5.40.5_n2_av

bsr_diff_nb_kde.5.40.5_n2_av<-BayesianSignedRank(as.matrix(diff_nb_kde.5.40.5_n2_av),-0.01,0.01)
bsr_diff_nb_kde.5.40.5_n2_av
## $winLeft
## [1] 0
## 
## $winRope
## [1] 0.008633333
## 
## $winRight
## [1] 0.9913667
bsr_diff_nb_kde.5.40.5_n2_av_odds.left<-bsr_diff_nb_kde.5.40.5_n2_av$winLeft/bsr_diff_nb_kde.5.40.5_n2_av$winRight
bsr_diff_nb_kde.5.40.5_n2_av_odds.left
## [1] 0
plot(rope(diff_nb_kde.5.40.5_n2_av,c(-0.01,0.01)))

#diff_nb_kde.5.40.5_n3_av<-nb_dataset_av - nb_kde.5.40.5_n3_av

#bsr_diff_nb_kde.5.40.5_n3_av<-BayesianSignedRank(as.matrix(diff_nb_kde.5.40.5_n3_av),-0.01,0.01)
#bsr_diff_nb_kde.5.40.5_n3_av

#bsr_diff_nb_kde.5.40.5_n3_av_odds.left<-bsr_diff_nb_kde.5.40.5_n3_av$winLeft/bsr_diff_nb_kde.5.40.5_n3_av$winRight
#bsr_diff_nb_kde.5.40.5_n3_av_odds.left

#plot(rope(diff_nb_kde.5.40.5_n3_av,c(-0.01,0.01)))


diff_nb_kde.5.40.5_n4_av<-nb_dataset_av - nb_kde.5.40.5_n4_av

bsr_diff_nb_kde.5.40.5_n4_av<-BayesianSignedRank(as.matrix(diff_nb_kde.5.40.5_n4_av),-0.01,0.01)
bsr_diff_nb_kde.5.40.5_n4_av
## $winLeft
## [1] 0.8752667
## 
## $winRope
## [1] 0.01623333
## 
## $winRight
## [1] 0.1085
bsr_diff_nb_kde.5.40.5_n4_av_odds.left<-bsr_diff_nb_kde.5.40.5_n4_av$winLeft/bsr_diff_nb_kde.5.40.5_n4_av$winRight
bsr_diff_nb_kde.5.40.5_n4_av_odds.left
## [1] 8.066974
plot(rope(diff_nb_kde.5.40.5_n4_av,c(-0.01,0.01)))

#diff_nb_kde.5.40.5_n5_av<-nb_dataset_av - nb_kde.5.40.5_n5_av

#bsr_diff_nb_kde.5.40.5_n5_av<-BayesianSignedRank(as.matrix(diff_nb_kde.5.40.5_n5_av),-0.01,0.01)
#bsr_diff_nb_kde.5.40.5_n5_av

#bsr_diff_nb_kde.5.40.5_n5_av_odds.left<-bsr_diff_nb_kde.5.40.5_n5_av$winLeft/bsr_diff_nb_kde.5.40.5_n5_av$winRight
#bsr_diff_nb_kde.5.40.5_n5_av_odds.left

#plot(rope(diff_nb_kde.5.40.5_n5_av,c(-0.01,0.01)))